ArticleJournal of biomolecular NMR2013
EZ-ASSIGN, a program for exhaustive NMR chemical shift assignments of large proteins from complete or incomplete triple-resonance data.
Article in Journal of biomolecular NMR, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- The disorderly conduct of Hsc70 and its interaction with the Alzheimer's-related Tau protein.The Journal of biological chemistry · 2018Article
- Backbone and methyl resonance assignments of the 42 kDa human Hsc70 nucleotide binding domain in the ADP state.Biomolecular NMR assignments · 2017Article
- Spectroscopic studies reveal that the heme regulatory motifs of heme oxygenase-2 are dynamically disordered and exhibit redox-dependent interaction with heme.Biochemistry · 2015Article
- Fast and accurate resonance assignment of small-to-large proteins by combining automated and manual approaches.PLoS computational biology · 2015Article
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4 authors.
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Abstract
For several of the proteins in the BioMagResBank larger than 200 residues, 60 % or fewer of the backbone resonances were assigned. But how reliable are those assignments? In contrast to complete assignments, where it is possible to check whether every triple-resonance Generalized Spin System (GSS) is assigned once and only once, with incomplete data one should compare all possible assignments and pick the best one. But that is not feasible: For example, for 200 residues and an incomplete set of 100 GSS, there are 1.6 × 10260 possible assignments. In "EZ-ASSIGN", the protein sequence is divided in smaller unique fragments. Combined with intelligent search approaches, an exhaustive comparison of all possible assignments is now feasible using a laptop computer. The program was tested with experimental data of a 388-residue domain of the Hsp70 chaperone protein DnaK and for a 351-residue domain of a type III secretion ATPase. EZ-ASSIGN reproduced the hand assignments. It did slightly better than the computer program PINE (Bahrami et al. in PLoS Comput Biol 5(3):e1000307, 2009) and significantly outperformed SAGA (Crippen et al. in J Biomol NMR 46:281-298, 2010), AUTOASSIGN (Zimmerman et al. in J Mol Biol 269:592-610, 1997), and IBIS (Hyberts and Wagner in J Biomol NMR 26:335-344, 2003). Next, EZ-ASSIGN was used to investigate how well NMR data of decreasing completeness can be assigned. We found that the program could confidently assign fragments in very incomplete data. Here, EZ-ASSIGN dramatically outperformed all the other assignment programs tested.
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